Digital imaging methods have now come to play a decisive role in medical diagnostics and intervention. Whereas digital techniques have been used from the start in diagnostic methods such as in computer tomography, magnetic resonance, ultrasound and in nuclear medicine, the transition to digital imaging is now taking place to a large extent in “conventional” x-ray methods, such as mammography, angiography or cardiology. Digital x-ray detectors have thus been changing classical radiography for many years. A very wide variety of technologies have already been in use for a long time or are due on the market very soon. These digital technologies include systems such as image intensifier camera systems, based on television or CCD (Charged Coupled Devices) cameras, memory foil systems with integrated or external read-out unit, systems with optical coupling of the converter foil to CCDs or CMOS chips, selenium-based detectors with electrostatic readout or solid-state detectors with active readout matrices and direct or indirect conversion of the x-ray radiation. The last-mentioned solid-state detectors (FD) in particular have undergone extensive development in recent years for use in digital x-ray imaging. A detailed overview of different systems or the general operation of direct or indirect-operation solid-state detectors is given in “Flachbilddetektoren in the Röntgendiagnostik” (Flat Panel Detectors in x-ray diagnostics), Radiologe 43 (2003) P. 340-350).
The permanent request from practical user experience is for better editing of the digital image in order to present the diagnostic content to its optimum effect and thereby to simplify and to accelerate diagnosis. Furthermore a significant objective of digital image processing is the editing of the x-ray image to reduce the radiation burden on the patient and on the examiner. In this case image processing functions as an intermediary in cases in which image information is present in a form which is inaccessible to the eye as a result of physiological characteristics of human vision. In addition to resolution, two significant parameters for an optimum image adjustment are the signal level and the contrast. In this case what is known as windowing provides assistance in compensating for the contrast capability of the eye which is restricted to appr. 27-28 gray levels, in that a spreading of the subareas of the image over the entire light density area of the illumination medium is undertaken and thereby its full dynamics exploited. With the current high digital resolution which is already the norm of up to 14 bits and thereby 16384 gray levels, the parameters for windowing are becoming even more important. If the windowing is too narrow or if the optimum level is not selected, image content disappears, if windowing is too wide the image contrast is too low and details are more difficult to distinguish. As already mentioned at the start, with x-ray devices on the other hand with almost delay-free digitization, such as for example with x-ray devices with flat-panel detectors, image processing is used to make dose control (e.g. for fluoroscopic examinations at high image rates of approximately 30 images/s) possible. In this case the image content is analyzed automatically and the generator settings (e.g. high voltage, tube current, filter) are obtained for the subsequent series of images. At this point this control task must even be performed by a digital image processing, since unlike with older technologies of image amplifiers, no separate optical signal can be derived here which would be able to be used for control tasks.
Various options are known from the prior art for setting the correct window values. Thus U.S. Pat. No. 4,827,492 describes a device for manual gray value windowing in which the window width is set with one operating element and the center of the window, the upper or the lower window border are set with another operating element. However processes which execute automatically are desirable which save time and money in clinical operation.
Another widespread option for automatic windowing in x-ray systems is the exclusive use of so-called organ buttons which use a preset, empirically-determined set of parameters for the relevant recording area. The disadvantage of this process is the high operator effort caused by the organ buttons. Furthermore the imaging conditions which differ individually because of the previously defined parameters are not taken into account, the parameters set can thus only represent a compromise.
A method is described in U.S. Pat. No. 5,351,306 in which, by determining statistical parameters in evaluation fields extending lengthwise in parallel to the border of the image, the position of insertions can be found. This fact that overradiation remains unconsidered and rotated insertions cannot be detected means that the optimum results are not always obtained with this type of windowing.
A method is known from U.S. Pat. No. 5,150,421 in which the histogram compensation described in literature and generally known (even distribution of the grey values) is performed in a slightly modified form. With this non-linear gray value transformation a restriction to the relevant image area is however also necessary. This is resolved by weighting the individual pixels differently. A requirement is that insertions and overradiation are extremely bright or dark and are also mainly to be found at the edges of the image. Pixels close to the edge of the image as well as those with extreme grey values are also weighted less for histogram compensation than those which lie closer to the center of the image or which have less extreme grey values. Furthermore an object contours detection is proposed which is based on the detection of large changes to gray values in the image. The disadvantages of such a method are that this non-linear gray value transformation changes the character of the image. Furthermore it is not always true to assume that relevant areas of the image always lie close to the center of the image or do not have any extreme gray values. In addition insertions cannot be reliably detected by an object contour detection simply by detecting large gray value changes in the image without further measures.
A method is known from DE-A1-197 42 152 for windowed presentation of medical images in which insertions and/or overradiations can be recognized and extracted and only for the relevant parts of the image recorded in this way can their window sizes be determined by determining their minimum and maximum values. In these cases overradiation and/or insertions are completely extracted by recognizing geometrical structures, which also causes the removal of pixels in the edge area of the relevant parts of the image. Furthermore a method is described through which, starting from the edge areas, insertions, caused by a diaphragm can be extracted. In this case pixels are investigated step-by-step to the center of the image to see if they exceed a threshold as regards their gray value. The approaches described here refer back to the recognition of geometrical structures, edges, contours.